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Global Mobile Artificial Intelligence Market to reach USD 90.12 billion by the end of 2030

Global Mobile Artificial Intelligence Market Size study & Forecast, by Technology (7 nm, 10 nm, 20-28 nm, Others), by Application (Smartphones, Cameras, Drones, Automobile, Robotics, AR/VR, Others) and Regional Analysis, 2023-2030

Product Code: ICTNGT-35536638
Publish Date: 15-11-2023
Page: 200

Global Mobile Artificial Intelligence Market is valued at approximately USD 13.40 billion in 2022 and is anticipated to grow with a healthy growth rate of more than 26.9% over the forecast period 2023-2030. Mobile Artificial Intelligence (AI) is the integration of artificial intelligence technologies and capabilities into mobile devices such as smartphones, tablets, and wearable gadgets. It involves the deployment of AI algorithms and machine learning models directly on these devices, allowing them to perform complex tasks and make intelligent decisions locally, without the need for a constant internet connection or reliance on cloud-based AI services. The Mobile Artificial Intelligence Market is expanding because of factors such as the increasing penetration of mobile devices, the rise of cognitive computing and the increasing number of AI applications.

Mobile devices constantly collect data through sensors such as GPS, accelerometers, and cameras which generates huge amount of data. It includes location information, user preferences, behavioral patterns, and more. The sheer volume of data generated by mobile devices allows AI algorithms to learn and adapt, making applications smarter and more intuitive, thus rising penetration of mobile devices is driving the market growth. According to Statista, the number of smartphone mobile network subscriptions worldwide in year 2021 stood at 6165.06 million which increased to 6421.78 million in year 2022 and it is projected to reach 77436 million by year 2028. The rising smartphone mobile network subscriptions indicate the rising penetration of mobile devices, resulting in market growth. In addition, rising investment in AI research and development, and growing mergers and partnerships between big tech companies for product development are creating new opportunities for market growth. However, the premium pricing of AI Processors stifles market growth throughout the forecast period of 2023-2030.

The key regions considered for the Global Mobile Artificial Intelligence Market study includes Asia Pacific, North America, Europe, Latin America, and Middle East & Africa. North America dominated the market in 2022 owing to the high concentration of market participants, with numerous companies actively contributing to technological advancements. As a result of these companies’ ongoing innovations, the region is poised to become a frontrunner in technology adoption and a hub for leading AI solution providers specializing in mobile applications, primarily serving the North American market. Whereas, Asia Pacific is projected to register the fastest growth owing to factors such as rising smartphone penetration, and rising investment in Artificial Intelligence (AI) technologies in the region.

Major market player included in this report are:
Intel Corporation
Microsoft Corporation
Google LLC
Apple Inc
Samsung Electronics Co. Ltd.
Nvidia Corporation
International Business Machines Corporation
Qualcomm Technologies Inc
MediaTek Inc.
Huawei Technologies Co. Ltd.

Recent Developments in the Market:
Ø In March 2023, Qualcomm Technologies, Inc. introduced the Snapdragon 7+ Gen 2 Mobile Platform, setting the stage for exceptional premium experiences exclusive to the Snapdragon 7 series. This innovative platform unlocks a range of capabilities, including 4K HDR videography, enhanced low-light photography, seamless gaming, AI-powered enhancements, and rapid 5G and Wi-Fi connectivity. These remarkable features are driven by the outstanding CPU and GPU capabilities of the Snapdragon 7+ Gen 2, contributing to the expansion of its market share.
Ø In May 2023, IBM Watson technology has been integrated into SAP solutions to deliver fresh insights powered by artificial intelligence. This strategic integration aims to expedite innovation and enhance the efficiency and effectiveness of user interactions across the entire SAP solution portfolio.

Global Mobile Artificial Intelligence Market Report Scope:
ü Historical Data – 2020 – 2021
ü Base Year for Estimation – 2022
ü Forecast period – 2023-2030
ü Report Coverage – Revenue forecast, Company Ranking, Competitive Landscape, Growth factors, and Trends
ü Segments Covered – Technology, Application, Region
ü Regional Scope – North America; Europe; Asia Pacific; Latin America; Middle East & Africa
ü Customization Scope – Free report customization (equivalent up to 8 analyst’s working hours) with purchase. Addition or alteration to country, regional & segment scope*

The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within countries involved in the study.

The report also caters detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, it also incorporates potential opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players. The detailed segments and sub-segment of the market are explained below:

By Technology:
7 nm
10 nm
20-28 nm

By Application:

By Region:

North America


Asia Pacific
South Korea

Latin America

Middle East & Africa
Saudi Arabia
South Africa
Rest of Middle East & Africa

Chapter 1. Executive Summary
1.1. Market Snapshot
1.2. Global & Segmental Market Estimates & Forecasts, 2020-2030 (USD Billion)
1.2.1. Mobile Artificial Intelligence Market, by Region, 2020-2030 (USD Billion)
1.2.2. Mobile Artificial Intelligence Market, by Technology, 2020-2030 (USD Billion)
1.2.3. Mobile Artificial Intelligence Market, by Application, 2020-2030 (USD Billion)
1.3. Key Trends
1.4. Estimation Methodology
1.5. Research Assumption
Chapter 2. Global Mobile Artificial Intelligence Market Definition and Scope
2.1. Objective of the Study
2.2. Market Definition & Scope
2.2.1. Industry Evolution
2.2.2. Scope of the Study
2.3. Years Considered for the Study
2.4. Currency Conversion Rates
Chapter 3. Global Mobile Artificial Intelligence Market Dynamics
3.1. Mobile Artificial Intelligence Market Impact Analysis (2020-2030)
3.1.1. Market Drivers Increasing penetration of mobile devices Rise of cognitive computing Increasing number of AI applications
3.1.2. Market Challenges Premium pricing of AI Processors
3.1.3. Market Opportunities Rising investment in AI research and development Growing number of mergers and partnerships between big tech companies
Chapter 4. Global Mobile Artificial Intelligence Market Industry Analysis
4.1. Porter’s 5 Force Model
4.1.1. Bargaining Power of Suppliers
4.1.2. Bargaining Power of Buyers
4.1.3. Threat of New Entrants
4.1.4. Threat of Substitutes
4.1.5. Competitive Rivalry
4.2. Porter’s 5 Force Impact Analysis
4.3. PEST Analysis
4.3.1. Political
4.3.2. Economical
4.3.3. Social
4.3.4. Technological
4.3.5. Environmental
4.3.6. Legal
4.4. Top investment opportunity
4.5. Top winning strategies
4.6. COVID-19 Impact Analysis
4.7. Disruptive Trends
4.8. Industry Expert Perspective
4.9. Analyst Recommendation & Conclusion
Chapter 5. Global Mobile Artificial Intelligence Market, by Technology
5.1. Market Snapshot
5.2. Global Mobile Artificial Intelligence Market by Technology, Performance – Potential Analysis
5.3. Global Mobile Artificial Intelligence Market Estimates & Forecasts by Technology 2020-2030 (USD Billion)
5.4. Mobile Artificial Intelligence Market, Sub Segment Analysis
5.4.1. 7 nm
5.4.2. 10 nm
5.4.3. 20-28 nm
5.4.4. Others
Chapter 6. Global Mobile Artificial Intelligence Market, by Application
6.1. Market Snapshot
6.2. Global Mobile Artificial Intelligence Market by Application, Performance – Potential Analysis
6.3. Global Mobile Artificial Intelligence Market Estimates & Forecasts by Application 2020-2030 (USD Billion)
6.4. Mobile Artificial Intelligence Market, Sub Segment Analysis
6.4.1. Smartphones
6.4.2. Cameras
6.4.3. Drones
6.4.4. Automobile
6.4.5. Robotics
6.4.6. AR/VR
6.4.7. Others
Chapter 7. Global Mobile Artificial Intelligence Market, Regional Analysis
7.1. Top Leading Countries
7.2. Top Emerging Countries
7.3. Mobile Artificial Intelligence Market, Regional Market Snapshot
7.4. North America Mobile Artificial Intelligence Market
7.4.1. U.S. Mobile Artificial Intelligence Market Technology breakdown estimates & forecasts, 2020-2030 Application breakdown estimates & forecasts, 2020-2030
7.4.2. Canada Mobile Artificial Intelligence Market
7.5. Europe Mobile Artificial Intelligence Market Snapshot
7.5.1. U.K. Mobile Artificial Intelligence Market
7.5.2. Germany Mobile Artificial Intelligence Market
7.5.3. France Mobile Artificial Intelligence Market
7.5.4. Spain Mobile Artificial Intelligence Market
7.5.5. Italy Mobile Artificial Intelligence Market
7.5.6. Rest of Europe Mobile Artificial Intelligence Market
7.6. Asia-Pacific Mobile Artificial Intelligence Market Snapshot
7.6.1. China Mobile Artificial Intelligence Market
7.6.2. India Mobile Artificial Intelligence Market
7.6.3. Japan Mobile Artificial Intelligence Market
7.6.4. Australia Mobile Artificial Intelligence Market
7.6.5. South Korea Mobile Artificial Intelligence Market
7.6.6. Rest of Asia Pacific Mobile Artificial Intelligence Market
7.7. Latin America Mobile Artificial Intelligence Market Snapshot
7.7.1. Brazil Mobile Artificial Intelligence Market
7.7.2. Mexico Mobile Artificial Intelligence Market
7.8. Middle East & Africa Mobile Artificial Intelligence Market
7.8.1. Saudi Arabia Mobile Artificial Intelligence Market
7.8.2. South Africa Mobile Artificial Intelligence Market
7.8.3. Rest of Middle East & Africa Mobile Artificial Intelligence Market

Chapter 8. Competitive Intelligence
8.1. Key Company SWOT Analysis
8.1.1. Company 1
8.1.2. Company 2
8.1.3. Company 3
8.2. Top Market Strategies
8.3. Company Profiles
8.3.1. Intel Corporation Key Information Overview Financial (Subject to Data Availability) Product Summary Recent Developments
8.3.2. Microsoft Corporation
8.3.3. Google LLC
8.3.4. Apple Inc
8.3.5. Samsung Electronics Co. Ltd.
8.3.6. Nvidia Corporation
8.3.7. International Business Machine Corporation
8.3.8. Qualcomm Technologies Inc
8.3.9. MediaTek Inc.
8.3.10. Huawei Technologies Co. Ltd.
Chapter 9. Research Process
9.1. Research Process
9.1.1. Data Mining
9.1.2. Analysis
9.1.3. Market Estimation
9.1.4. Validation
9.1.5. Publishing
9.2. Research Attributes
9.3. Research Assumption

At Bizwit Research and Consultancy, we employ a thorough and iterative research methodology with the goal of minimizing discrepancies, ensuring the provision of highly accurate estimates and predictions over the forecast period. Our approach involves a combination of bottom-up and top-down strategies to effectively segment and estimate quantitative aspects of the market, utilizing our proprietary data & AI tools. Our Proprietary Tools allow us for the creation of customized models specific to the research objectives. This enables us to develop tailored statistical models and forecasting algorithms to estimate market trends, future growth, or consumer behavior. The customization enhances the accuracy and relevance of the research findings.
We are dedicated to clearly communicating the purpose and objectives of each research project in the final deliverables. Our process begins by identifying the specific problem or challenge our client wishes to address, and from there, we establish precise research questions that need to be answered. To gain a comprehensive understanding of the subject matter and identify the most relevant trends and best practices, we conduct an extensive review of existing literature, industry reports, case studies, and pertinent academic research.
Critical elements of methodology employed for all our studies include:
Data Collection:
To determine the appropriate methods of data collection based on the research objectives, we consider both primary and secondary sources. Primary data collection involves gathering information directly from various industry experts in core and related fields, original equipment manufacturers (OEMs), vendors, suppliers, technology developers, alliances, and organizations. These sources encompass all segments of the value chain within the specific industry. Through in-depth interviews, we engage with key industry participants, subject-matter experts, C-level executives of major market players, industry consultants, and other relevant experts. This allows us to obtain and validate critical qualitative and quantitative information while evaluating market prospects. AI and Big Data are instrumental in our primary research, providing us with powerful tools to collect, analyze, and derive insights from data efficiently. These technologies contribute to the advancement of research methodologies, enabling us to make data-driven decisions and uncover valuable findings.
In addition to primary sources, we extensively utilize secondary sources to enhance our research. These include directories, databases, journals focusing on related industries, company newsletters, and information portals such as Bloomberg, D&B Hoovers, and Factiva. These secondary sources enable us to identify and gather valuable information for our comprehensive, technical, market-oriented, and commercial study of the market. Additionally, we utilize AI algorithms to automate the collection of vast amounts of data from various sources such as surveys, social media platforms, online transactions, and web scraping. And employ Big Data technologies for storage and processing of large datasets, ensuring that no valuable information is missed during the data collection process.
Data Analysis:
Our team of experts carefully examine the gathered data using suitable statistical techniques and qualitative analysis methods. For quantitative analysis, we employ descriptive statistics, regression analysis, and other advanced statistical methods, depending on the characteristics of the data. This analysis may also incorporate the utilization of AI tools and big data analysis techniques to extract meaningful insights.
To ensure the accuracy and reliability of our findings, we extensively leverage data science techniques, which help us minimize discrepancies and uncertainties in our analysis. We employ Data Science to clean and preprocess the data, ensuring its quality and reliability. This involves handling missing data, removing outliers, standardizing variables, and transforming data into suitable formats for analysis. The application of data science techniques enhances our accuracy, efficiency, and depth of analysis, enabling us to stay competitive in dynamic market environments.
Market Size Estimation:
Our proprietary data tools play a crucial role in deriving our market estimates and forecasts. Each study involves the creation of a unique and customized model. The model incorporates the gathered information on market dynamics, technology landscape, application development, and pricing trends. AI techniques, such as machine learning and deep learning, aid us to analyze patterns within the data to identify correlations, trends, and relationships. By recognizing patterns in consumer behavior, purchasing habits, or market dynamics, our AI algorithms aid us in more precise estimations of market size. These factors are simultaneously analyzed within the model, allowing for a comprehensive assessment. To quantify their impact over the forecast period, correlation, regression, and time series analysis are employed.
To estimate and validate the market size, we employ both top-down and bottom-up approaches. The preference is given to a bottom-up approach, where key regional markets are analyzed as separate entities. This data is then integrated to obtain global estimates. This approach is crucial as it provides a deep understanding of the industry and helps minimize errors.
In our forecasting process, we consider various parameters such as economic tools, technological analysis, industry experience, and domain expertise. By taking all these factors into account, we strive to produce accurate and reliable market forecasts. When forecasting, we take into consideration several parameters, which include:
Market driving trends and favorable economic conditions
Restraints and challenges that are expected to be encountered during the forecast period.
Anticipated opportunities for growth and development
Technological advancements and projected developments in the market
Consumer spending trends and dynamics
Shifts in consumer preferences and behaviors.
The current state of raw materials and trends in supply versus pricing
Regulatory landscape and expected changes or developments.
The existing capacity in the market and any expected additions or expansions up to the end of the forecast period.
To assess the market impact of these parameters, we assign weights to each one and utilize weighted average analysis. This process allows us to quantify their influence on the market and derive an expected growth rate for the forecasted period. By considering these various factors and applying a weighted analysis approach, we strive to provide accurate and reliable market forecasts.
Insight Generation & Report Presentation:
After conducting the research, our experts analyze the findings in relation to the research objectives and the specific needs of the client. They generate valuable insights and recommendations that directly address the client’s business challenges. These insights are carefully connected to the research findings to provide a comprehensive understanding.
Next, we create a well-structured research report that effectively communicates the research findings, insights, and recommendations to the client. To enhance clarity and comprehension, we utilize visual aids such as charts, graphs, and tables. These visual elements are employed to present the data in an engaging and easily understandable format, ensuring that the information is accessible and visually appealing to the client. Our aim is to deliver a clear and concise report that conveys the research findings effectively and provides actionable recommendations to meet the client’s specific needs.

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